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05/12/2023
Online machine-learning forecast uncertainty estimation for sequential data assimilation
Quantifying forecast uncertainty is a key aspect of state-of-the-art num...
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03/18/2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensive...
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03/16/2023
Reduction of rain-induced errors for wind speed estimation on SAR observations using convolutional neural networks
Synthetic Aperture Radar is known to be able to provide high-resolution ...
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07/15/2022
Rain Rate Estimation with SAR using NEXRAD measurements with Convolutional Neural Networks
Remote sensing of rainfall events is critical for both operational and s...
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02/17/2022
Two-dimensional structure functions to characterize convective rolls in the marine atmospheric boundary layer from Sentinel-1 SAR images
We study the shape of convective rolls in the Marine Atmospheric Boundar...
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11/29/2021
Evaluation of Machine Learning Techniques for Forecast Uncertainty Quantification
Producing an accurate weather forecast and a reliable quantification of ...
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01/26/2021
Probability distributions for analog-to-target distances
Some properties of chaotic dynamical systems can be probed through featu...
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03/04/2020
Model error covariance estimation in particle and ensemble Kalman filters using an online expectation-maximization algorithm
The performance of ensemble-based data assimilation techniques that esti...
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10/18/2019
Coupling Oceanic Observation Systems to Study Mesoscale Ocean Dynamics
Understanding local currents in the North Atlantic region of the ocean i...
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07/30/2018
Joint Estimation of Model and Observation Error Covariance Matrices in Data Assimilation: a Review
This paper is a review of a crucial topic in data assimilation: the join...
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04/20/2018
An efficient particle-based method for maximum likelihood estimation in nonlinear state-space models
Data assimilation methods aim at estimating the state of a system by com...
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11/10/2017